Cooperative merging strategy for connected and automated vehicles at highway on-ramps

Xiao-Kui Guan; Mao-Bin Hu

doi:10.1117/12.2628488

22 April 2022 Cooperative merging strategy for connected and automated vehicles at highway on-ramps

Xiao-Kui Guan, Mao-Bin Hu

Proceedings Volume 12174, International Conference on Internet of Things and Machine Learning (IoTML 2021); 121740Q (2022) https://doi.org/10.1117/12.2628488
Event: International Conference on Internet of Things and Machine Learning (IoTML 2021), 2021, Shanghai, China

Abstract

Merging roadways are one of the main reasons for reducing highway traffic safety and transportation efficiency. This paper proposes a multi-vehicle cooperative driving strategy for on-ramp merging in the environment of connected and automated vehicles (CAVs). Based on the principle of first-in-first-out (FIFO), a new algorithm is designed to optimize the merging sequence of CAVs. The velocity profile of each CAV is planned according to the merging sequence to make CAVs pass through the merging zone smoothly and safely. Compared with the FIFO strategy under different traffic demands, the effectiveness of the proposed strategy is validated.

Citation Download Citation

Xiao-Kui Guan and Mao-Bin Hu "Cooperative merging strategy for connected and automated vehicles at highway on-ramps", Proc. SPIE 12174, International Conference on Internet of Things and Machine Learning (IoTML 2021), 121740Q (22 April 2022); https://doi.org/10.1117/12.2628488

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